Game strategies for decision making in hierarchical systems. II. Computer simulation of stochastic game


  • Petro A. Kravets Lviv Polytechnic National University, Lviv, Ukraine



decision making, hierarchical system, conditions of uncertainty, stochastic game, computer modelling


An algorithm for solving a stochastic game for decision making in hierarchical systems under uncertainty is developed. An analysis of the results of computer modeling of a stochastic game for autocratic, anarchic and democratic hierarchical decision making systems with the binary tree structure is performed. It has been established that autocratic-centric hierarchical systems have the smallest training time for achieving a close-to-consensus solution. The influence of parameters on the convergence of the game method in the process of finding a consensus or a majoritarian collective solution is studied.

Author Biography

Petro A. Kravets, Lviv Polytechnic National University, Lviv

Petro Alekseevich Kravets,

Cand. Tech. Sci. (Ph.D.), an associate professor at the Department of Information Systems and Networks of Lviv Polytechnic National University, Lviv, Ukraine.

Research areas: game models and decision-making methods under conditions of uncertainty, multi-agent systems.


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Mathematical methods, models, problems and technologies for complex systems research